Staff Data Engineer - Enterprise Platform, AI foundations
About this role
SentinelOne is building an AI-native cybersecurity platform that unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response. The engineering team is developing the enterprise data platform, focusing on modern data engineering, analytics enablement, governance, and AI-ready data foundations at petabytes scale.
As a Staff Data Engineer, you will own and improve the trusted data foundation supporting executive reporting, product insights, revenue operations, finance, and GTM workflows. You will build and troubleshoot production-grade data pipelines, enhance data quality and observability, and partner with various business stakeholders to deliver scalable data solutions.
This role exists to support the company's rapid scaling in an AI-enabled enterprise environment by maintaining robust data infrastructure and reliable pipelines. Someone who is relentlessly curious, comfortable collaborating across technical and business teams, and experienced in managing large-scale cloud data systems will succeed in this position.
What you will do
- Build, maintain, and troubleshoot production-grade data pipelines across source systems, cloud data platforms, and business-facing data products handling petabytes of data.
- Support and improve critical data workflows using BigQuery, GCP, Kestra, Nexla, DataHub, Looker, Tableau, and Workato.
- Improve data quality, observability, freshness monitoring, schema validation, reconciliation, alerting, and operational reliability for critical datasets.
- Participate in production support for business-critical data workflows, including incident response, root-cause analysis, and runbook development.
- Strengthen data governance and discoverability through metadata management, lineage, ownership, certification, and metric definitions.
- Partner with Analytics, BI, Product, Finance, GTM, IT, Security, and Engineering stakeholders to deliver trusted datasets and AI-ready data foundations.
- Leverage AI tools responsibly to increase engineering productivity across SQL support, Python development, debugging, testing, and operational analysis.
What you need
- Advanced SQL and Python proficiency for building, optimizing, troubleshooting, automating, and testing data pipelines across large datasets.
- Proven experience building and supporting batch or near-real-time ingestion pipelines using tools such as Nexla, Workato, Fivetran, APIs, or custom pipelines.
- Hands-on experience with cloud-based data stacks such as GCP and BigQuery or comparable alternatives in the AWS ecosystem.
- Experience with production dataset management, performance tuning, IAM, service accounts, and dev/prod environment separation.
- Experience with workflow orchestration tools such as Kestra, Airflow, dbt Cloud, or similar scheduling and dependency tools.
- Deep understanding of dimensional modeling and data quality practices including reconciliation, schema validation, and freshness monitoring.
- Familiarity with metadata management, lineage, data catalogs, semantic layers, and engineering best practices such as Git, CI/CD, testing, and code reviews.
Benefits
- Restricted Stock Units (RSUs) and Employee Stock Purchase Plan (ESPP)
- Performance-based bonus
- Flexible time off and standard 5 weeks PTO
- Private medical care benefit, life and disability insurance, and pension insurance contribution
- Global home office allowance and meal allowance
- Wellbeing allowance and MultiSport benefit program
Skills and tech stack
Questions candidates ask
What is the remote work and office policy for this role?
The role offers hybrid work in Prague, Brno, or remote in CZ and SK. Only Prague-based employees are required to work from the office at least two days per week.
What tools and technologies will I be working with?
You will work with BigQuery, GCP, Kestra, Nexla, DataHub, Looker, Tableau, and Workato across Salesforce, billing, ARR, customer data, and finance domains. The role requires advanced SQL and Python proficiency for building and optimizing data pipelines.
What teams will I collaborate with in this position?
You will partner across Analytics, BI, Product, Finance, GTM, IT, Security, and Engineering stakeholders to deliver trusted datasets, AI-ready data foundations, and scalable data solutions.